A visual representation for knowledge structures
HYPERTEXT '89 Proceedings of the second annual ACM conference on Hypertext
An integrated environment for knowledge acquisition
Proceedings of the 6th international conference on Intelligent user interfaces
Knowledge Retrieval and the World Wide Web
IEEE Intelligent Systems
Knowledge retrieval as specialized inference (artificial intelligence, sorted logic)
Knowledge retrieval as specialized inference (artificial intelligence, sorted logic)
Knowledge logistics in information grid environment
Future Generation Computer Systems - Special issue: Semantic grid and knowledge grid: the next-generation web
A Logical Framework of Knowledge Retrieval with Fuzziness
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Cognitive support for ontology modeling
International Journal of Human-Computer Studies - Protégé: community is everything
Unifying Reasoning and Search to Web Scale
IEEE Internet Computing
ARMS: an automatic knowledge engineering tool for learning action models for AI planning
The Knowledge Engineering Review
KBS development through ontology mapping and ontology driven acquisition
Proceedings of the 4th international conference on Knowledge capture
Enabling experts to build knowledge bases from science textbooks
Proceedings of the 4th international conference on Knowledge capture
VODKA: Variant objects discovering knowledge acquisition
Expert Systems with Applications: An International Journal
Supporting Literature Exploration with Granular Knowledge Structures
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Hi-index | 0.00 |
Many of the component failures occurring in service can be delayed by better incorporation of tribological principles into engineering design and maintenance. However, the concept of tribology has not yet penetrated successfully into the industry in general and there is an urgent need for the practical tribology design criteria and transference of tribological knowledge to the engineering designer and maintenance engineer. Knowledge based system offers great potential for effecting tribological knowledge transfer and promoting improved design practice and maintenance strategy. In this present work, the development and implementation of a tribological failure knowledge model (KM) for steam power plant equipment is reported. This failure KM assists the maintenance engineer and design engineer for evolution of an effective maintenance strategy and better, reliable, safe and productive design. The KM has been implemented using Protege 3.0 Beta, JDK 1.4 and Java Swing Package. The model is applied to steam turbine failure in a power plant application.